In Silico Predictability of Toxicity Parameters Using the OECD QSAR Toolbox of Some Components of Cannabis sativa

Abstract: In this paper, the quantitative structure‐activity relationship predictive models (QSAR) are presented: the prediction model for some of the main components of cannabis sativa, acute toxicity LD50 (n=45, r2=0.917, q2=0.902), chronic toxicity LOAEL (n=35, r2=0.911, q2=0.868), NOAEL (n=22, r2=0.964, q2=0.937), LOEL (n=26, r2=0.911, q2=0.863) and NOEL (n=25, r2=0.867, q2=0.802), in addition to carcinogenicity and mutagenicity effects. Only for the case of LD50, the values reported in the literature of the delta 9‐THC compound present in Cannabis sativa were taken into account and this model was applied to the other compounds present in the plant, which we consider the most relevant since they fell from the allowed domain for QSAR Toolbox to predict the LD50 of each of them, while the other additional endpoints were established according to the methodology that marks the QSAR Toolbox software. The application of these models and predictions allowed us to predict the permissible daily exposure (PDE) and acceptable daily intake (ADI) values of some of the cannabis components. This work aims to present important elements of the toxicology of some of the components of the plant that serve only as a reference and does not intend to favor or inhibit the use of cannabis for medicinal or recreational use.

Object Details

• Location: Deutsche Nationalbibliothek Frankfurt am Main
• Extent: Online-Ressource
• Language: Englisch

References and Relationships

• Bibliographic citation: In Silico Predictability of Toxicity Parameters Using the OECD QSAR Toolbox of Some Components of Cannabis sativa ; volume:8 ; number:3 ; year:2023 ; extent:9 ; ChemistrySelect ; 8, Heft 3 (2023) (gesamt 9)

Contributors, Places and Time

• Creator: Vázquez‐Valadez, Víctor Hugo ; Oliva‐Arellano, María Virginia ; Martínez‐Soriano, Pablo Arturo ; Hernández‐Serda, Manuel Alejandro ; Velázquez‐Sánchez, Ana María ; Concepción Rodríguez‐Maciel, José ; Angeles, Enrique

Further information

• DOI: 10.1002/slct.202204079
• URN: urn:nbn:de:101:1-2023012014311839222124
• Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Last update: 15.08.2025, 7:31 AM CEST